Context-Aware Computing Research Papers - Academia.edu (original) (raw)

2025, Societies

According to KPMG, Internet of Things (IoT) technology was among the top 10 technologies of 2019. It has been growing at a significant pace, influencing and disrupting several application domains. It is expected that by 2025, 75.44 billion devices will be connected to the Internet. These devices generate massive amounts of data which, when harnessed using the power of data science (DS) techniques and approaches such as artificial intelligence (AI) and machine learning (ML), can provide significant benefits to economy, society, and people. Examples of areas that are being disrupted are digital marketing and retail commerce services in smart cities. This paper presents a vision for Marketing 4.0 that is underpinned by disruptive digital technologies such as IoT and DS. We present an analysis of the current state of the art in IoT and DS via the three pillars of marketing: namely, people, products, and places. We propose a blueprint architecture for developing a Marketing 4.0 solution that is underpinned by IoT and DS. We conclude the paper by highlighting the open challenges that need to be addressed in order to realise the Marketing 4.0 blueprint architecture, including supporting the integration of IoT data concerning people, products, and places and using DS to make efficient and effective recommendations.

2025, Proceedings of the Tenth International Conference on Enterprise Information Systems

When different devices and applications start to work with one another, physical and behavioral aspects from the environment have to be taken into account when designing a system. It is impractical, if not impossible, to list all possible devices, applications and new characteristics and behaviors that might emerge as result from the autonomy of each part from the parts of the system, different data interpretation and self-organization capability. In order to cope with this difficulty, this paper combines the contributions from different works as a way to improve the modeling process of this type of computational environment.

2025

Mobile commerce is heading for advanced fourth generation (4G) mobile systems. However, rapid development of ubiquitous computing technology can implement and complement the 4G mobile systems. It enables anticipation that ubiquitous computing technology creates the new commerce, so called ubiquitous commerce. This paper analyzes the characteristics of mobile commerce service and ubiquitous computing service, and then extracts the core requirements for ubiquitous commerce. Moreover, this paper suggests technical requirements for the ubiquitous commerce. These requirements can lead the development of technology for the future and suggest the milestone that mobile commerce in present heads for.

2025

スマートフォンや情報家電といったネットワーク接続可能なデバイスにより実世界の多種多様な場面で情報処理を活用できるようになった．それに伴って，多種多様な用途を対象としたアプリケーションが求められるようになっている．そこで，多様化するアプリケーションをユーザ自身が開発できるよう，プログラミングに慣れていないユーザであっても，自らのアプリケーションへの要求を自らで満たすことが可能なマッシュアップフレームワークIDUMO を提案する．IDUMO フレームワークでは，マッシュアップに必要不可欠な機能である，（1）統一的な入出力インタフェースの定義，（2）プログラム実行モデルの差異の吸収，（3）容易な開発方法，を提供する．本論文では，IDUMO フレームワークの設計について述べ，アプリケーション開発のケーススタディにより有用性を示す

2025, somoslibres.org

En este artículo daremos a conocer en forma descriptiva y técnica el proceso de implementación de portales WAP, utilizando herramientas de Software Libre para ser aplicada en una Ofician de Relaciones Públicas que brinda información y noticias a sus usuarios. Esta solución técnica permite la integración de varios lenguajes y herramientas de Software Libre capaces de presentar la información en un dispositivo móvil como es un Celular.

2025, Wave-Based Memory Systems

We present Mem|8, a novel memory system architecture that utilizes wave-based patterns and grid structures to process, store, and adapt memories across multiple modalities. Unlike traditional memory systems that rely on static storage or simple decay mechanisms, Mem|8 implements a dynamic wave-based approach where memories propagate and interact like waves in an ocean, with importance acting as amplitude and temporal relationships forming interference patterns. This approach enables more natural memory dynamics including reinforcement, decay, and pattern emergence. We augment this with comprehensive emotional modeling, ethical safeguards, and collaborative features like Hot Tub Mode for safe exploration. Our experimental results show that Mem|8 outperforms traditional memory architectures on tasks requiring temporal reasoning, emotional intelligence, and ethical decision making.

2025

Nous sommes à l'aube d'une énorme explosion de données et la quantité à traiter par les entreprises est de plus en plus grande. Pour faire face à ce chalenge, Google a développé MapReduce, un modèle de programmation parallèle qui est en train de devenir l'outil de facto pour l'analyse des systèmes Big Data. Bien que dans une certaine mesure son utilisation est déjà très répandue dans l'industrie, garantir les performances d'un système aussi complexe pose de grands problèmes et sa gestion nécessite un haut niveau d'expertise. Cet article répond à ces défis en proposant le premier système autonome qui garantit des contraintes de temps de réponse pour une charge de travail MapReduce simultanée. Nous développons le premier modèle dynamique d'une grappe MapReduce. De plus, un contrôle en boucle fermée est conçu et implémenté pour garantir un temps de réponse donné. Un contrôle d'anticipation de type "feedforward" est également rajouté pour améliorer la réponse du système en présence de perturbations, en l'occurrence, la variation du nombre de clients. L'approche est validée en ligne sur une grappe MapReduce avec 40 noeuds utilisant une charge de travail intensive de type Business Intelligence. Nos expériences montrent que le contrôle ainsi conçu peut garantir les contraintes de temps de réponse.

2025

Este artigo apresenta um estudo da Computacao Autonomica (CA) aplicado na literatura de sensoriamento urbano. A analise revela que o ponto de vista da CA ainda nao foi totalmente explorado por tais trabalhos. Nesse sentido, um mecanismo de autoadapacao com base no modelo de MAPE-K e proposto com o objetivo de proporcionar um componente generico capaz de tratar os pontos identificados. Como avaliacao preliminar, o mecanismo proposto foi incorporado na implementacao da arquitetura UrboSenti para dispositivos moveis e desktop visando discutir as observacoes encontradas. Palavras-chave: Computacao Autonoma, Sensoriamento Urbano, Sistemas Autoadaptativos, Computacao Movel.

2025

Recommendation for public radio is a challenging area. In contrast to music recommendation, which has been intensively discussed in research as well as in practice, recommendation for radio has some special additional challenges as it mixes diverse formats, such as news, articles, audio dramas, biographies, etc. Focusing on the interaction design of a radio player, we bring up and discuss these special challenges and find that in a radio recommender context, optimal interaction design has conflicting issues with optimal algorithmic design.

2025, IEEE Access

In this paper, we address the neighborhood identification problem in the presence of a large number of heterogeneous contextual features. We formulate our research as a problem of queue wait time prediction for taxi drivers at airports and investigate heterogeneous factors related to time, weather, flight arrivals, and taxi trips. The neighborhood-based methods have been applied to this type of problem previously. However, the failure to capture the relevant heterogeneous contextual factors and their weights during the calculation of neighborhoods can make existing methods ineffective. Specifically, a driver intelligence-biased weighting scheme is introduced to estimate the importance of each contextual factor that utilizes taxi drivers' intelligent moves. We argue that the quality of the identified neighborhood is significantly improved by considering the relevant heterogeneous contextual factors, thus boosting the prediction performance (i.e., mean prediction error < 0.09 and median prediction error < 0.06). To support our claim, we generated an airport taxi wait time dataset for the John F. Kennedy International Airport by fusing three real-world contextual datasets, including taxi trip logs, passenger wait times, and weather conditions. Our experimental results demonstrate that the presence of heterogeneous contextual features and the drivers' intelligence-biased weighting scheme significantly outperform the baseline approaches for predicting taxi driver queue wait times. INDEX TERMS Heterogeneous contextual features, neighborhood identification, wait time prediction, feature weighting.

2025, Symulacja w Badaniach i Rozwoju

2025

> 1.Especificaciones y estándares en e-learning > 2.Objetos de aprendizaje > 3.Especificaciones y estandarización: aspectos y proceso > 4.Especificaciones y estándares más utilizados en e-learning > 5.Perfiles de aplicación > 6.LMS y utilidades compatibles con las especificaciones y los estándares > 7.Conclusiones > 8.Agradecimientos > 9.Algunas referencias

2025, 2006 Pervasive Health Conference and Workshops

which could be sufficient for some applications. We discuss how these results can be used in the design of activity-aware hospital information systems.

2025, Mobile Networks and Applications

Hospitals are convenient settings for the deployment of context-aware applications. The information needs of hospital workers are highly dependent on contextual variables, such as location, role and activity. While some of these parameters can be easily determined, others, such as activity are much more complex to estimate. This paper describes an approach to estimate the activity being performed by hospital workers. The approach is based on information gathered from a workplace study conducted in a hospital, in which 196 h of detailed observation of hospital workers was recorded. Contextual information, such as the location of hospital workers, artifacts being used, the people with whom they collaborate and the time of the day, is used to train a back propagation neural network to estimate hospital workers activities. The activities estimated include clinical case assessment, patient care, preparation, information management, coordination and classes and certification. The results indicate that the user activity can be correctly estimated 75% of the time (on average) which is good enough for several applications. We discuss how these results can be used in the design of activity-aware applications, arguing that recent advances in pervasive and networking technologies hold great promises for the deployment of such applications.

2025

This paper describes an approach for a Transparent API (Application Programming Interface) based in Magic LensTM. Magic Lenses are movable filters that displace over an application work area and show new views of objects viewed through that area. The transparent API proposed is a visualization mechanism that have tools distinguished by: unobstructed view of the objects in the working area, use of typical interaction elements with user of traditional interfaces, active process of data, and the possibility to use it as an additional element in any graphic user interface (GUI)

2025

My project is based on research done in the anthropology and geography departments by myself, Dr. Zimmerman and Courtney Singleton pertaining to homeless encampments in Indianapolis. This poster presentation illustrates locations of selected encampments and their access to service providers. Geographic information system (GIS) technologies were used to conduct a network analysis that visually shows access to services and quantifies travel time and network distance to selected service locations. The analysis presented is based on data collected by my colleagues from subjects in one specific camp describing preferred travel routes, distances traveled and services needed-prescription medication for example. I plan to apply this analytical method to other encampments to create a model of hypothetical routes based upon tow paths, walking trails and street networks.

2025, Journal of Applied Information Science

The latest developments in Artificial Intelligence (AI) and the Internet of Things (IoT) have transformed the current context of technology and society. AI and IoT are now indispensable components of modern businesses, industries, and daily life. In AI, breakthroughs have been achieved in natural language processing (NLP), computer vision, and machine learning algorithms. Cutting-edge NLP models, such as GPT-3, have demonstrated remarkable language understanding capabilities, enabling more sophisticated chatbots, virtual assistants, and automated content generation. Computer vision advancements have led to improved object recognition, image synthesis, and video analysis, enabling applications in areas like autonomous vehicles, surveillance, and medical imaging. The convergence of AI and IoT has been a game-changer in various industries. IoT devices equipped with AI capabilities enhance data analysis and decision-making processes. AI-powered IoT solutions have revolutionized healthcare by enabling remote patient monitoring, predictive maintenance in industrial settings, and smart home automation for consumers. This amalgamation has opened up possibilities for real-time data-driven insights and autonomous systems. Challenges related to AI and IoT persist, including data privacy concerns, cybersecurity risks, and ethical considerations. As the deployment of AI and IoT continues to expand, addressing these issues becomes crucial to ensure the responsible and ethical use of these technologies. In conclusion, the latest developments in AI and IoT have significantly impacted the current context of technology and society. They have unlocked unprecedented opportunities for innovation, automation, and data-driven decision-making. However, careful consideration of ethical implications and proactive measures to address security concerns are essential to fully harness the potential of these transformative technologies in a sustainable and inclusive manner.

2025, Revista Ibérica de Sistemas e Tecnologias de Informação

Las personas con discapacidad tienen dificultades en el desplazamiento y las actividades cotidianas. Esta investigación presenta una revisión sistemática de la literatura del uso de la visión artificial con realidad aumentada para dar soporte al desplazamiento de personas con discapacidad visual. Se exploraron 92 artículos publicados en los últimos 5 años sobre soluciones para el desplazamiento de personas con discapacidad visual usando las tecnologías mencionadas. A partir de los resultados obtenidos en esta revisión, quedó claro que la tecnología más usada como solución en el desarrollo de visión artificial son los sensores. De igual manera, se identificó que los principales criterios del impacto de la visión artificial considerados en la elaboración de los sistemas de solución son la navegación, orientación, encuestas de satisfacción y objetos identificados. Por último, se dan una serie de recomendaciones que pueden ser consideradas en el desarrollo de futuros artículos sobre este tema. Palabras-clave: Realidad aumentada, visión artificial, discapacidad visual, detección de obstáculos, navegación con visión artificial.

2025, Georgia Tech GVU Technical Report GIT- …

Ubiquitous computing (ubicomp) is an emerging paradigm for interaction between people and computers. A guiding principle of ubicomp is to break away from desktop computing to provide computational services to a user when and where required. Although there has been a lot of experimental work in ubicomp, there has been little effort to define an agenda in ubicomp for HCI researchers. In this paper, we attempt to remedy that problem by defining the space of ubicomp applications in terms of the level of user mobility and transparency ...

2025, Exybris Pipeline: A Modular AI Framework for Industrial, Military, and Context-Driven Memory Retrieval Optimization

The Exybris Pipeline introduces a modular architecture for optimizing contextual memory retrieval and scoring in AI systems, targeting industrial, military, and strategic applications. Leveraging dynamic memory adaptation, contextual scoring, and optimized retrieval mechanisms, Exybris enhances AI model efficiency while minimizing computational overhead. Certain architectural innovations and implementation details are protected under intellectual property frameworks to safeguard their strategic value and are omitted here to maintain confidentiality. This paper introduces the conceptual framework of the Exybris Pipeline, outlining its theoretical foundations and strategic applications. The initial Proof of Concept (PoC) is currently being developed and will be iteratively refined based on experimental results. Interested parties are encouraged to contact the authors for potential partnerships under confidentiality agreements.
Under CC-BY-NC-ND 4.0 License. Please refer to the full CC BY-NC 4.0 terms for details : Commercial use is not permitted. The version publish here is not listed under CC BY-NC 4.0 due to platform constraints. To access to the officially licensed CC BY-NC 4.0 version, please refer to the Zenodo record : https://doi.org/10.5281/zenodo.14942197

2025, Neural Network Applications in IoT-Driven Coffee Customization: Learning Beverage Preferences

The beverage coffee obtains global popularity because people prefer to drink it according to distinct preferences. Each person seeks a different coffee strength level while choosing milk type or temperature along with a preferred level of sweetness. The combination of Neural Networks with IoT enables smart coffee machines to acquire individual member preferences because they alter manual settings in traditional devices. Neural networks provide machines with the ability to gather patterns from consumers' coffee selection choices. Previous choices allow the system to learn which drinks users prefer: strong espresso beverages for the mornings and sweet lattes during the afternoon. The system adopts more efficient methods of operation through continual observation of daily user patterns. The Internet of Things allows the machine to establish connections that automate coffee preparation through devices, including smartphones and smart home assistants, as well as other kitchen technologies. Real-time data helps the system modify coffee production through mechanisms that involve time factors along with user moods or climatic conditions. As per temperature variations, the machine generates prepared hot cappuccino beverages in chilly mornings yet makes iced coffee during warm afternoons. The system obtains user feedback to enhance the precision of preference adjustments. The integration of AI systems and IoT technology leads to smarter coffee production, which results in decreased waiting time and precision. The system will improve through advanced features such as voice command capabilities, health recommendation services, and ingredient tracking functionality to deliver more tailored experiences. Technology supports coffee lovers to obtain their personalized cups automatically without requiring any input from them.

2025, Personal and Ubiquitous Computing

Your article is protected by copyright and all rights are held exclusively by Springer-Verlag London Limited. This e-offprint is for personal use only and shall not be self-archived in electronic repositories. If you wish to selfarchive your work, please use the accepted author's version for posting to your own website or your institution's repository. You may further deposit the accepted author's version on a funder's repository at a funder's request, provided it is not made publicly available until 12 months after publication.

2025

This paper compares an emergent interaction modality for the In-Vehicle Infotainment System (IVIS), i.e., gesturing on the steering wheel, with two more popular modalities in modern cars: touch and speech. We conducted a betweensubjects experiment with 20 participants for each modality to assess the interaction performance with the IVIS and the impact on the driving performance. Moreover, we compared the three modalities in terms of usability, subjective workload and emotional response. The results showed no statically significant differences between the three interaction modalities regarding the various indicators for the driving task performance, while significant differences were found in measures of IVIS interaction performance: users performed less interactions to complete the secondary tasks with the speech modality, while, in average, a lower task completion time was registered with the touch modality. The three interfaces were comparable in all the subjective metrics.

2025, Proceedings of the 2007 IEEE Three-Rivers Workshop on Soft Computing in Industrial Applications, Passau, Germany

Times, they say, they are a-changing, and they bring with them both grand new opportunities and new challenging societal problems. One such problem is costeffective healthcare. The traditional approaches, though effective, are often too expensive, hence novel mechanisms are currently being sought. One such family of mechanisms is the one that makes use of interreality coupling physical-reality objects and properties with virtual-life entities such as avatars and their attributes. This introduces a number of technical ...

2025, 2008 IEEE/IFIP International Conference on Embedded and Ubiquitous Computing

We envisage future context-aware applications will dynamically adapt their behaviors to various context data from sources in wide-area networks, such as the Internet. Facing the changing context and the sheer number of context sources, a data management system that supports effective source organization and efficient data lookup becomes crucial to the easy development of context-aware applications. In this paper, we propose the design of a new context data management system that is equipped with query processing capabilities. We encapsulate the context sources into physical spaces belonging to different context spaces and organize them as peers in semantic overlay networks. Initial evaluation results of an experimental system prototype demonstrate the effectiveness of our design.

2025, 2008 International Conference on Intelligent Sensors, Sensor Networks and Information Processing

Applications in context-aware computing continuously change their operations based on sensor data or services provided by various physical spaces in the real world, such as persons, shops and homes. We propose a gateway framework for physical spaces in this paper, which serves as a middleware platform for context-aware applications to access data from sensor networks deployed in these spaces. The gateway contains a number of components that facilitate the sensor data acquisition, processing and communication in context-aware applications. These include diversified services with plug-in management, a query processing engine with reasoning capability, and the global connection and local detection between gateways.

2025, Discrete Applied Mathematics

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2025, Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

2025, CONTEXT-AWARE MODELING OF DYNAMIC RESOURCE MANAGEMENT IN CLOUD INFRASTRUCTURE

Dynamic resource management in cloud environments is crucial for maintaining efficient service delivery and performance. This study models the dynamic allocation of resources in cloud systems, where resources are distributed based on current server load, network conditions, and user request patterns. The proposed model utilizes the Calculus of Context-aware Ambients (CCA) to simulate interactions between different entities (ambients) within the cloud environment, including Cloud Service Manager, Servers, Services, and User Requests, and Network conditions. This model demonstrates how adaptive and dynamic resource management in cloud environments can be optimized. By allowing servers and network components to adapt to changing conditions, resources can be reallocated and workload redistributed in real time, leading to improved efficiency and performance across the cloud system.

2025

Cloud computing is a rapidly developing information technology concept. Within a few years, cloud computing has become the fastest emerging technology. It is internet based computing software and resources are shared and information is provided to computers on demand. It is a low cost computing entity that uses the advanced business or service models such as SaaS(Software as Service), PaaS (Platform as Service), IaaS (Infrastructure as Service) and deployment models such as Public, Private , Hybrid and Community cloud to distribute the powerful computing capability to end user. This paper highlights the emergence of cloud computing from a style of computing to a on demand full fledged service model. Comparative study of various service and deployment models for cloud computing is also presented.

2025

The KnowSense framework, presented in this work, supports monitoring behavioral aspects of individuals in goal-oriented scenarios, within controlled, pervasive environments. Semantic Web technologies, such as OWL 2, are extensively employed in KnowSense to represent sensor observations and application domain specifics as well as to implement hybrid activity recognition and problem detection solutions. Although the framework can be beneficial in a variety of domains that require multi-sensing and goal-oriented data analytics such as smart homes, it is currently applied in the eminent field of healthcare. In this proof-of-concept health application, it provides the semantic models and intelligent detection of Instrumental Activities of Daily Living (IADLs) to assist in the clinical assessment of autonomy at different stages of dementia.

2025

Tyson (2010) conducted research on 100 students using the Hospital Anxiety and Depression Scale (HADS) and the Physical Activity Questionnaire (PAQ). He concluded that students who engaged in more exercise had better mental health. Other studies have confirmed his findings, and have demonstrated how a student’s well-being is related to their success in building relationships and maintaining academic studies. On the other hand, students that do not engage in physical activity often experience negative wellbeing, including difficulty concentrating, fatigue, and psychological disorders. The objectives of this study are to determine if the strength of association between daily emotion and activity participation is similar across college students, and how physical activity and travel mobility relate to well-being. The Experience Sampling Method (ESM), developed by Csikszentmihalyi, Larson, and Prescott (1977) will be used in conjunction with an accelerometer and global positioning system...

2025

A continuación se muestra una tabla-resumen comparando de manera breve y concisa las cuatro aplicaciones, según las características y funcionalidades que ofrecen.

2025, International Journal of Computer Science & Applications

Today’s mobile devices have become increasingly powerful with enhanced features such as increased CPU power and memory, internet connectivity in multiple ways (multi-homing) and interfacing with external peripheral devices (for instance GPS receiver, medical sensors). The proliferation of these mobile devices combined with an increasing willingness of users to share information available on and around mobile device (e.g. location, user

2025, Anais do VIII Simpósio Brasileiro de Computação Ubíqua e Pervasiva (SBCUP 2016)

A mobilidade dos usuários e o crescente número de espaços inteligentes tanto pessoais quanto fixos, fomentados também pela Internet das Coisas e Web das Coisas, podem levar à sobreposição de espaços inteligentes, onde um determinado objeto inteligente pode ser utilizado em diferentes espaços inteligentes. Além disso, espaços inteligentes são complexos e difíceis de modelar e manter, pois, entre outros fatores, precisam lidar com diferentes objetos inteligentes. Este trabalho apresenta o uso de técnicas de Engenharia Dirigida por Modelos para possibilitar a modelagem de cenários de computação ubíqua, considerando a coexistência entre espaços inteligentes fixos e pessoais. A validação da proposta se deu pela modelagem de um cenário com o auxílio de uma ferramenta gráfica de modelagem construída para produzir modelos em conformidade com o metamodelo proposto.

2024

The optimisation of the passenger travel experience, particularly in dense urban environments, has become increasingly important. An essential approach to optimising passenger travel experience is predicting travel time. This helps streamline the travel process, making it more predictable, less stressful, and efficient, significantly enhancing the passenger travel experience. Using data from New York City (NYC) Taxi and Limousine Commission (TLC) High Volume For-Hire Vehicle Trip Records, this study explores the prediction of total trip time. Various features were analysed by integrating weather data, holiday schedules, and trip timing information, and machine learning models were developed. Among the models tested, Random Forest regression stood out with moderate accuracy. The results indicate that while some level of trip time prediction is achievable, there are significant challenges in accurately forecasting due to the variability and complexity of urban travel patterns.

2024, ACM SIGARCH Computer Architecture News

Hardware and timing complexities of MAC unit to perform arithmetic operation like addition or multiplication especially in the field of Digital Signal Processing (DSP) or Elliptic Curve Cryptography (ECC) are the major issues to the designer. The multiplication operation is essential and abundant in DSP Applications. In order to achieve maximum implementation efficiency and timing performance, designing a DSP systems is critical and frequently presents a significant challenge to hardware engineers. There are certain Multiplier that simplifies this challenge by abstracting away FPGA device specifics, while maintaining the required maximum performance and resource efficiency. These multipliers are able to perform parallel multiplication and hence constant coefficient multiplication, both with differing implementation styles. Again with the aid of instantaneous resource estimation, hardware engineers can rapidly select the optimal solution for their system. The latest additions to the ...

2024, Lecture Notes in Computer Science

Context-aware computing can play a major role to improve the services of mobile networking systems. In this paper, we focus on optimizing handover decisions based not only on the signal quality, but also on the knowledge about the context of mobile devices and networks. Since context information and context processing evolves fast, we propose a flexible, integrated approach for context management, which can adapt in several ways. Our architecture encompasses active platforms in network nodes and mobile devices, distributed context management components on these platforms, and service deployment for network services. This flexible architecture is able to actively deploy different handover services. It can manage different kinds of context information and allow mobile devices to be always connected to the most suitable access network. Our architecture is validated in a prototype implementation.

2024, Personal and Ubiquitous Computing

Context detection for mobile users plays a major role for enabling novel, human-centric interfaces. For this, we introduce a context detection scheme for disseminated, computer empowered sensors, referred to as Smart-Its . Context-detection takes place without requiring any central point of control, and supports push as well as pull modes. Our solution is based on an in-network composition approach relying on so-called smart context-aware packets (sCAPs). sCAPs travel thru a sensor network governed by an enclosed retrieving plan, specifying which sensors to visit for gaining a specific piece of context information. For enhanced flexibility, the retrieving plan itself may be dynamically altered in accordance to past sensor readings.

2024, Personal and Ubiquitous Computing

2024

The evolution of mobile communication systems to 3G and beyond introduces requirements for flexible, customized, and ubiquitous multimedia service provision to mobile users. One must be able to know at any given time the network status, the user location, the profiles of the various entities (users, terminals, network equipment, services) involved and the policies that are employed within the system. Namely, the system must be able to cope with a large amount of context information. Present paper focuses on location and context awareness in mobile service provisioning and proposes a flexible and innovative model for user profiling. The innovation is based on the enrichment of common user profiling architectures to include location and other contextual attributes, so that enhanced adaptability and personalization can be achieved. For each location and context instance an associated User Profile instance is created and hence, service provisioning is adapted to the User Profile instance that better apply to the current context. The generic model, the structure and the content of this location-and contextsensitive User Profile, along with some related implementation issues, are discussed.

2024

In "Skating on Thin Ice," Frohlich and Oppenheimer (2006) describe a phenomenon they observed in laboratory experiments on the production of public goods that is rarely discussed in the literature. They report individual contributions to the public good are often inconsistent over time, appearing to fluctuate between two distinct contribution levels. Although they conjecture that individuals have complex context-dependent preferences, they did not develop a full specification of the theory. We develop an agent-based simulation of these conjectures, provide a possible specification of a theory of complex context-dependent preferences, and demonstrate how this theory can, in fact, generate the pattern of contributions observed by Frohlich and Oppenheimer. We then conduct sensitivity analyses, examining the behavior generated by fourteen scenarios. Two main theories are considered: that inconsistent contributions arise either from a deterministic avoidance of exploitation or from a probabilistic response to exploitation. The former theory clearly fails, the latter theory, under certain conditions, does produce the observed pattern of contributions. Two simple alternative theories are also considered, that of a highly-stylized "probabilistic guilt" and of goal-oriented but non-utility maximizing behavior (with stable preferences). Both alternatives, under certain conditions, are also able to generate the observed pattern. We develop an analysis of situations in which the predictions of these theories diverge and suggest that one could discriminate between them in laboratory settings. Finally, we consider a possibly fruitful relationship between simulation and experimentation to consider the implications of one's models and conjectures.

2024, Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

Tabletop displays are gaining interests in gaming environments. Computer Game in the genre of board games, competitive actions, real-time strategies are amongst those that are suitable for tabletop displays. Currently most games developed for tabletops use physical objects with markings as the controllers and standard touch and gestures as the inputs. To extend the present limits of gestures and touch, we present an implementation of high performance sensor-based input modality as an extension to tabletop displays. The additional input modality has the capability to sense and track users' bodies while they are interacting with the table. This paper outlines the configuration of the sensors, the tracking accuracy test result and informal evaluations of the system. We emphasise the simplicity of sensor configuration, cost, robustness and high performance in the design of tabletop sensor systems. To demonstrate the capability of our system, we developed a computer game ''Body Pong'' where each player controls a paddle assigned automatically to him/her by moving his/her position left and right. The game demonstrates how contextawareness adapts when number of users changes during game play.

2024, Journal of Computer Science

Problem statement: The databases introduce the digital era the fact that requirement to maintain large and ample data. The growth of information development and improvement that pursued it transformed the databases into a global reality. This study enquired and described the vital role of storing the context data to an appropriate database in the area of context aware computing. It also addson limitations of the existing relational and object relational databases with respect to context aware computing. Approach: This article examines traditional database like relational database, object relational database and spatial database. It helps to make an optimal decision while choosing the database for context aware applications. Results: All the traditional databases are compared with context aware features like semantic support, ease of transaction of large data, query optimization, reasoning support, formality, scalability, spatial data and xml support. Conclusion: This study confirmed that using object relational database along with ontology is more apt for storing the context data for context aware computing applications.

2024

Currently, there is congestion in the parking lots they are usually known, mainly in nearby locations to public and private institutions in the city; Also, when visiting a place little known occurs the difficulty of finding a parking; this causes loss of time of drivers until find a place available. In response, the development of this work whose main objective is to develop an Android mobile app for search of places available and a route to a nearby parking lot, in the city of Loja was raised. The methodology used was mobile-d, oriented small groups and rapid development cycles. Upon completion of this work an Android mobile application that allows viewing of the parking from the location of the device, from an alternate location entered by the user, or all parking of the city; also allows searching for a parking for their business name and finding a nearby parking lot with its respective route and the option to display the route through maps app or navigation app, apps of Android....

2024

We present an emerging approach of Mobile Social Spaces (MOSS) that intends to improve the ways in which people communicate in the modern world. Pervasive content and service creation and provisioning, in particular for dynamically changing social groups, is a complex task and subject to varying locations of individuals, of the complete group and its context. MOSS tries to remove some of the obstacles in this area and defines a range of functionalities that will support dynamic ubiquitous creation and instantiation of community content and services.

2024, 07-07-2019

Tout le monde est un génie. Mais si on juge un poisson sur sa capacité à grimper à un arbre, il passera sa vie à croire qu'il est stupide.